UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Published in:

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2305233


Registration ID:
515063

Page Number

c218-c224

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Title

Analyze and evaluate the learning Performance of Students in Educational Institution using AI

Abstract

Abstract: One of the most promising 21st-century approaches to smart education is the smart classroom. The Internet of Things, artificial intelligence, and cloud computing, among other amazing technologies, allow for the continuous analysis and evaluation of student learning performance in classrooms today. We developed a complete management system for computer vision in smart classrooms after realizing this opportunity. Through the smart classroom solution, students can request an absence, which their teachers can then approve or deny online. Additionally, the dashboard displays a summary of the enrolled and absent students. The managers or teachers can then download the attendance list for use in additional reports. The dashboard has filters for each student as well as weeks, months, and years. Face recognition technology can also be used in security to quickly alert the guards of suspicious intrusions and automatically detect them. The device can also monitor the student's emotions and display them in real-time on the chart. Managers or teachers might assess their teaching effectiveness using this data. The three following primary points are the emphasis of our contributions. First of all, our suggested system can compile data from many devices, analyse it, and display it on an interactive dashboard. The dashboard, in addition to the management system, features a user-friendly design that enables administrators and teachers to easily use technology even if they are not familiar with it. Also used and improved are the AI Modules taught in the classroom. Particularly, compared to the other applications, the emotion detection model is more accurate with a score of 73.6%.

Key Words

Smart Classroom, Internet of Things, Artificial Intelligence, Cloud Computing.

Cite This Article

"Analyze and evaluate the learning Performance of Students in Educational Institution using AI ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.c218-c224, May-2023, Available :http://www.jetir.org/papers/JETIR2305233.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Analyze and evaluate the learning Performance of Students in Educational Institution using AI ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppc218-c224, May-2023, Available at : http://www.jetir.org/papers/JETIR2305233.pdf

Publication Details

Published Paper ID: JETIR2305233
Registration ID: 515063
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: c218-c224
Country: MUMBAI, MAHARASTRA, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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